Interpretation of primary care physicians' attitude regarding rotavirus immunisation using diffusion of innovation theories.

To evaluate primary care physicians' attitude towards implementation of rotavirus (RV) immunisation into the Swiss immunisation schedule, an eight-question internet-based questionnaire was sent to the 3799 subscribers of InfoVac, a nationwide web-based expert network on immunisation issues, which reaches >95% of paediatricians and smaller proportions of other primary care physicians. Five demographic variables were also inquired. Descriptive statistics and multivariate analyses for the main outcome "acceptance of routine RV immunisation" and other variables were performed. Diffusion of innovation theory was used for data assessment. Nine-hundred seventy-seven questionnaires were returned (26%). Fifty percent of participants were paediatricians. Routine RV immunisation was supported by 146 participants (15%; so called early adopters), dismissed by 620 (64%), leaving 211 (21%) undecided. However, when asked whether they would recommend RV vaccination to parents if it were officially recommended by the federal authorities and reimbursed, 467 (48.5%; so called early majority) agreed to recommend RV immunisation. Multivariate analysis revealed that physicians who would immunise their own child (OR: 5.1; 95% CI: 4.1-6.3), hospital-based physicians (OR: 1.6; 95% CI: 1.1-2.3) and physicians from the French (OR: 1.6; 95% CI: 1.2-2.3) and Italian speaking areas of Switzerland (OR: 2.5; 95% CI: 1.1-5.8) were more likely to support RV immunisation. Diffusion of innovation theory predicts a >80% implementation if approximately 50% of a given population support an innovation. Introduction of RV immunisation in Switzerland is likely to be successful, if (i) the federal authorities issue an official recommendation and (ii) costs are covered by basic health care insurance.

Glutathione precursor N-acetyl-cysteine modulates EEG synchronization in schizophrenia patients: a double-blind, randomized, placebo-controlled trial.

Glutathione (GSH) dysregulation at the gene, protein, and functional levels has been observed in schizophrenia patients. Together with disease-like anomalies in GSH deficit experimental models, it suggests that such redox dysregulation can play a critical role in altering neural connectivity and synchronization, and thus possibly causing schizophrenia symptoms. To determine whether increased GSH levels would modulate EEG synchronization, N-acetyl-cysteine (NAC), a glutathione precursor, was administered to patients in a randomized, double-blind, crossover protocol for 60 days, followed by placebo for another 60 days (or vice versa). We analyzed whole-head topography of the multivariate phase synchronization (MPS) for 128-channel resting-state EEGs that were recorded at the onset, at the point of crossover, and at the end of the protocol. In this proof of concept study, the treatment with NAC significantly increased MPS compared to placebo over the left parieto-temporal, the right temporal, and the bilateral prefrontal regions. These changes were robust both at the group and at the individual level. Although MPS increase was observed in the absence of clinical improvement at a group level, it correlated with individual change estimated by Liddle's disorganization scale. Therefore, significant changes in EEG synchronization induced by NAC administration may precede clinically detectable improvement, highlighting its possible utility as a biomarker of treatment efficacy. TRIAL REGISTRATION: ClinicalTrials.gov NCT01506765.

Les méthodes d'ajustement dans les modèles d'évaluation de la mortalité hospitalière. Partie 1, Etude descriptive : document de travail

Suite à la demande du Président de la République de disposer d'indicateurs de mortalité en établissements de santé » (discours du 18 septembre 2008 sur le thème de la politique de la santé et de la réforme du système de soins), la Direction de la recherche, des études, de l'évaluation et des statistiques (DREES) a piloté en 2009, en lien avec la Direction générale de l'offre de soins (DGOS) et la Haute autorité de santé (HAS), l'instruction des aspects méthodologiques relatifs à la construction de ces indicateurs de mortalité. Cette revue de littérature portant sur les différentes méthodes d'ajustement a été réalisée dans ce cadre, à la demande conjointe de la DREES et de la HAS.Ce rapport décrit les méthodes et modèles d'estimation et d'ajustement de la mortalité hospitalière identifiées dans la littérature.Il ressort de cette revue, que d'une manière générale, trois questions méthodologiques majeures préoccupent les épidémiologistes, les chercheurs et les décideurs s'intéressant à l'indicateur de la mortalité hospitalière : i) premièrement, sur l'opportunité d'établir l'indicateur de mortalité hospitalière à partir de groupes de population de patients homogènes définis par des pathologies et/ou des procédures médicales/chirurgicales cibles ; ii) deuxièmement, sur le type d'approche analytique et de l'intérêt de prendre en compte plusieurs niveaux dans l'analyse statistique ; iii) enfin troisièmement, sur le choix des variables d'ajustement permettant de contrôler les différences de case-mix entre plusieurs établissements ou groupes de patients pour réaliser des comparaisons. [Ed.]

Official Positions for FRAX® clinical regarding smoking from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

The worldwide prevalence of smoking has been estimated at about 50% in men, and 10% in women, with larger variations among different populations studied. Smoking has been shown to affect many organ systems resulting in severe morbidity and increased mortality. In addition, smoking has been identified as a predictor of ten-year fracture risk in men and women, largely independent of an individual's bone mineral density. This finding has eventually lead to incorporation of this risk factor into FRAX®, an algorithm that has been developed to calculate an individual's ten-year fracture risk. However, only little, or conflicting data is available on a possible association between smoking dose, duration, length of time after cessation, type of tobacco and fracture risk, limiting this risk factor's applicability in the context of FRAX®.

Inferring landscape effects on dispersal from genetic distances: how far can we go?

Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.

Joint Official Positions of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX(®). Executive Summary of the 2010 Position Development Conference on Interpretation and use of FRAX® in clinical practice.

The International Society for Clinical Densitometry (ISCD) and the International Osteoporosis Foundation (IOF) convened the FRAX(®) Position Development Conference (PDC) in Bucharest, Romania, on November 14, 2010, following a two-day joint meeting of the ISCD and IOF on the "Interpretation and Use of FRAX(®) in Clinical Practice." These three days of critical discussion and debate, led by a panel of international experts from the ISCD, IOF and dedicated task forces, have clarified a number of important issues pertaining to the interpretation and implementation of FRAX(®) in clinical practice. The Official Positions resulting from the PDC are intended to enhance the quality and clinical utility of fracture risk assessment worldwide. Since the field of skeletal assessment is still evolving rapidly, some clinically important issues addressed at the PDCs are not associated with robust medical evidence. Accordingly, some Official Positions are based largely on expert opinion. Despite limitations inherent in such a process, the ISCD and IOF believe it is important to provide clinicians and technologists with the best distillation of current knowledge in the discipline of bone densitometry and provide an important focus for the scientific community to consider. This report describes the methodology and results of the ISCD-IOF PDC dedicated to FRAX(®).

Relationship of hyperactivity/inattention with adiposity and lifestyle characteristics in preschool children.

We performed a cross-sectional study in 450 nonreferred preschool children aged 4 to 6 years to assess the association between hyperactivity/inattention with adiposity and lifestyle characteristics. Measurements included scores of hyperactivity/inattention, adiposity, objectively measured physical activity, television viewing, and eating habits. Higher scores of hyperactivity/inattention were associated with lower percentage body fat, higher levels of physical activity, and less time spent in sedentary activity (all P ≤ .01). However, higher scores of hyperactivity/inattention were also associated with more television viewing and less healthy eating habits (all P ≤ .04). Except for some selected eating habits (P ≥ .07), those relationships remained significant after adjustment for age, sex, and sociodemographic confounders. To conclude, higher scores of hyperactivity/inattention are linked to different lifestyle characteristics that may in part contribute to a future development of overweight/obesity. Precise mechanisms explaining these associations and possible preventive approaches should be further investigated.

P value and the theory of hypothesis testing: an explanation for new researchers.

In the 1920s, Ronald Fisher developed the theory behind the p value and Jerzy Neyman and Egon Pearson developed the theory of hypothesis testing. These distinct theories have provided researchers important quantitative tools to confirm or refute their hypotheses. The p value is the probability to obtain an effect equal to or more extreme than the one observed presuming the null hypothesis of no effect is true; it gives researchers a measure of the strength of evidence against the null hypothesis. As commonly used, investigators will select a threshold p value below which they will reject the null hypothesis. The theory of hypothesis testing allows researchers to reject a null hypothesis in favor of an alternative hypothesis of some effect. As commonly used, investigators choose Type I error (rejecting the null hypothesis when it is true) and Type II error (accepting the null hypothesis when it is false) levels and determine some critical region. If the test statistic falls into that critical region, the null hypothesis is rejected in favor of the alternative hypothesis. Despite similarities between the two, the p value and the theory of hypothesis testing are different theories that often are misunderstood and confused, leading researchers to improper conclusions. Perhaps the most common misconception is to consider the p value as the probability that the null hypothesis is true rather than the probability of obtaining the difference observed, or one that is more extreme, considering the null is true. Another concern is the risk that an important proportion of statistically significant results are falsely significant. Researchers should have a minimum understanding of these two theories so that they are better able to plan, conduct, interpret, and report scientific experiments.

Official Positions for FRAX® clinical regarding rheumatoid arthritis from Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

Rheumatoid arthritis is the only secondary cause of osteoporosis that is considered independent of bone density in the FRAX(®) algorithm. Although input for rheumatoid arthritis in FRAX(®) is a dichotomous variable, intuitively, one would expect that more severe or active disease would be associated with a greater risk for fracture. We reviewed the literature to determine if specific disease parameters or medication use could be used to better characterize fracture risk in individuals with rheumatoid arthritis. Although many studies document a correlation between various parameters of disease activity or severity and decreased bone density, fewer have associated these variables with fracture risk. We reviewed these studies in detail and concluded that disability measures such as HAQ (Health Assessment Questionnaire) and functional class do correlate with clinical fractures but not morphometric vertebral fractures. One large study found a strong correlation with duration of disease and fracture risk but additional studies are needed to confirm this. There was little evidence to correlate other measures of disease such as DAS (disease activity score), VAS (visual analogue scale), acute phase reactants, use of non-glucocorticoid medications and increased fracture risk. We concluded that FRAX(®) calculations may underestimate fracture probability in patients with impaired functional status from rheumatoid arthritis but that this could not be quantified at this time. At this time, other disease measures cannot be used for fracture prediction. However only a few, mostly small studies addressed other disease parameters and further research is needed. Additional questions for future research are suggested.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

Group selection and kin selection: two concepts but one process.

In a recent paper, Traulsen and Nowak use a multilevel selection model to show that cooperation can be favored by group selection in finite populations [Traulsen A, Nowak M (2006) Proc Natl Acad Sci USA 103:10952-10955]. The authors challenge the view that kin selection may be an appropriate interpretation of their results and state that group selection is a distinctive process "that permeates evolutionary processes from the emergence of the first cells to eusociality and the economics of nations." In this paper, we start by addressing Traulsen and Nowak's challenge and demonstrate that all their results can be obtained by an application of kin selection theory. We then extend Traulsen and Nowak's model to life history conditions that have been previously studied. This allows us to highlight the differences and similarities between Traulsen and Nowak's model and typical kin selection models and also to broaden the scope of their results. Our retrospective analyses of Traulsen and Nowak's model illustrate that it is possible to convert group selection models to kin selection models without disturbing the mathematics describing the net effect of selection on cooperation.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Official Positions for FRAX® clinical regarding falls and frailty: can falls and frailty be used in FRAX®? From Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

Risk factors for fracture can be purely skeletal, e.g., bone mass, microarchitecture or geometry, or a combination of bone and falls risk related factors such as age and functional status. The remit of this Task Force was to review the evidence and consider if falls should be incorporated into the FRAX® model or, alternatively, to provide guidance to assist clinicians in clinical decision-making for patients with a falls history. It is clear that falls are a risk factor for fracture. Fracture probability may be underestimated by FRAX® in individuals with a history of frequent falls. The substantial evidence that various interventions are effective in reducing falls risk was reviewed. Targeting falls risk reduction strategies towards frail older people at high risk for indoor falls is appropriate. This Task Force believes that further fracture reduction requires measures to reduce falls risk in addition to bone directed therapy. Clinicians should recognize that patients with frequent falls are at higher fracture risk than currently estimated by FRAX® and include this in decision-making. However, quantitative adjustment of the FRAX® estimated risk based on falls history is not currently possible. In the long term, incorporation of falls as a risk factor in the FRAX® model would be ideal.

Hierarchical modeling gave plausible estimates of associations between metabolic syndrome and components of antiretroviral therapy.

OBJECTIVE: Hierarchical modeling has been proposed as a solution to the multiple exposure problem. We estimate associations between metabolic syndrome and different components of antiretroviral therapy using both conventional and hierarchical models. STUDY DESIGN AND SETTING: We use discrete time survival analysis to estimate the association between metabolic syndrome and cumulative exposure to 16 antiretrovirals from four drug classes. We fit a hierarchical model where the drug class provides a prior model of the association between metabolic syndrome and exposure to each antiretroviral. RESULTS: One thousand two hundred and eighteen patients were followed for a median of 27 months, with 242 cases of metabolic syndrome (20%) at a rate of 7.5 cases per 100 patient years. Metabolic syndrome was more likely to develop in patients exposed to stavudine, but was less likely to develop in those exposed to atazanavir. The estimate for exposure to atazanavir increased from hazard ratio of 0.06 per 6 months' use in the conventional model to 0.37 in the hierarchical model (or from 0.57 to 0.81 when using spline-based covariate adjustment). CONCLUSION: These results are consistent with trials that show the disadvantage of stavudine and advantage of atazanavir relative to other drugs in their respective classes. The hierarchical model gave more plausible results than the equivalent conventional model.